Investigating the relationship between adverse events and infrastructure development in an active war theater using soft computing techniques

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dc.authoridBozkurt, Halil -- 0000-0002-4400-4519
dc.contributor.authorÇakıt, Erman
dc.contributor.authorKarwowski, Waldemar
dc.contributor.authorBozkurt, Halil
dc.contributor.authorAhram, Tareq
dc.contributor.authorThompson, William
dc.contributor.authorMikusinski, Piotr
dc.contributor.authorLee, Gene
dc.date.accessioned13.07.201910:50:10
dc.date.accessioned2019-07-29T19:27:46Z
dc.date.available13.07.201910:50:10
dc.date.available2019-07-29T19:27:46Z
dc.date.issued2014
dc.departmentMühendislik Fakültesi
dc.description.abstractThe purpose of this paper is to investigate the relationship between adverse events and infrastructure development investments in an active war theater by using soft computing techniques including fuzzy inference systems (FIS), artificial neural networks (ANNs), and adaptive neuro-fuzzy inference systems (ANFIS) where the accuracy of the predictions is directly beneficial from an economic and humanistic point of view. Fourteen developmental and economic improvement projects were selected as independent variables. A total of four outputs reflecting the adverse events in terms of the number of people killed, wounded or hijacked, and the total number of adverse events has been estimated. The results obtained from analysis and testing demonstrate that ANN, FIS, and ANFIS are useful modeling techniques for predicting the number of adverse events based on historical development or economic project data. When the model accuracy was calculated based on the mean absolute percentage error (MAPE) for each of the models, ANN had better predictive accuracy than FIS and ANFIS models, as demonstrated by experimental results. For the purpose of allocating resources and developing regions, the results can be summarized by examining the relationship between adverse events and infrastructure development in an active war theater, with emphasis on predicting the occurrence of events. We conclude that the importance of infrastructure development projects varied based on the specific regions and time period. (C) 2014 Elsevier B.V. All rights reserved.
dc.description.sponsorshipOffice of Naval Research [1052339]
dc.description.sponsorshipThis study was supported in part by Grant no. 1052339, Complex Systems Engineering for Rapid Computational Socio-Cultural Network Analysis, from the Office of Naval Research. The authors acknowledge the helpful guidance of ONR program management, and the contributions of the technical team.
dc.identifier.doi10.1016/j.asoc.2014.09.028
dc.identifier.endpage214en_US
dc.identifier.issn1568-4946
dc.identifier.issn1872-9681
dc.identifier.scopusqualityQ1
dc.identifier.startpage204en_US
dc.identifier.urihttps://doi.org/10.1016/j.asoc.2014.09.028
dc.identifier.urihttps://hdl.handle.net/20.500.12451/5928
dc.identifier.volume25en_US
dc.identifier.wosWOS:000344460600017
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofApplied Soft Computing Journal
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectInfrastructure Development
dc.subjectAdverse Events
dc.subjectSoft Computing
dc.subjectArtificial Neural Networks (ANNs)
dc.subjectFuzzy Inference System (FIS)
dc.subjectAdaptive Neuro-fuzzy Inference Systems (ANFIS)
dc.titleInvestigating the relationship between adverse events and infrastructure development in an active war theater using soft computing techniques
dc.typeArticle

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